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Causal associations of hypothyroidism with frozen shoulder: a two-sample bidirectional Mendelian randomization study

BMC Musculoskeletal Disorders volume 25, Article number: 693 (2024) Cite this article

Abstract

Background

Many studies have investigated the association between hypothyroidism and frozen shoulder, but their findings have been inconsistent. Furthermore, earlier research has been primarily observational, which may introduce bias and does not establish a cause-and-effect relationship. To ascertain the causal association, we performed a two-sample bidirectional Mendelian randomization (MR) analysis.

Methods

We obtained data on “Hypothyroidism” and “Frozen Shoulder” from Summary-level Genome-Wide Association Studies (GWAS) datasets that have been published. The information came from European population samples. The primary analysis utilized the inverse-variance weighted (IVW) method. Additionally, a sensitivity analysis was conducted to assess the robustness of the results.

Results

We ultimately chose 39 SNPs as IVs for the final analysis. The results of the two MR methods we utilized in the investigation indicated that a possible causal relationship between hypothyroidism and frozen shoulder. The most significant analytical outcome demonstrated an odds ratio (OR) of 1.0577 (95% Confidence Interval (CI):1.0057–1.1123), P = 0.029, using the IVW approach. Furthermore, using the MR Egger method as a supplementary analytical outcome showed an OR of 1.1608 (95% CI:1.0318–1.3060), P = 0.017. Furthermore, the results of our sensitivity analysis indicate that there is no heterogeneity or pleiotropy in our MR analysis. In the reverse Mendelian analysis, no causal relationship was found between frozen shoulders and hypothyroidism.

Conclusion

Our MR analysis suggests that there may be a causal relationship between hypothyroidism and frozen shoulder.

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Background

Frozen shoulder, also known as adhesive capsulitis, is a common shoulder condition. Patients with frozen shoulder usually experience severe shoulder pain and diffuse shoulder stiffness, which is usually progressive and can lead to severe limitations in daily activities, especially with external rotation of the shoulder joint [1]. The incidence of the disease is difficult to ascertain because of its insidious onset and the fact that many patients do not choose to seek medical attention. It is estimated to affect about 2% to 5% of the population, with women affected more commonly than men (1.6:1.0) [2, 3]. The peak occurrence of frozen shoulder is typically between the ages of 40 and 60, with a positive family history present in around 9.5% of cases [4]. However, the underlying etiology and pathophysiology of frozen shoulder remains unclear.

The prevalence of frozen shoulder has been reported to be higher in certain diseases such as dyslipidemia [5], diabetes [6, 7], and thyroid disorders [4, 8]. The relationship between diabetes and frozen shoulder has been established through epidemiological studies [9,10,11]. However, the relationship between thyroid disease and frozen shoulder remains unclear. Thyroid disorders include hyperthyroidism, hypothyroidism, thyroiditis, subclinical hypothyroidism, and others. Previously, some studies reported the connection between frozen shoulders and thyroid dysfunction. However, the conclusions of these studies are not consistent [4, 12,13,14,15,16]. In addition, these studies are primarily observational and susceptible to confounding variables. Traditional observational studies can only obtain correlations, not exact causal relationships [17].

MR is a technique that utilizes genetic variants as instrumental variables (IVs) of exposure factors to determine the causal relationship between exposure factors and outcomes [17, 18]. MR operates similarly to a randomized controlled trial as genetic variants adhere to Mendelian inheritance patterns and are randomly distributed in the population [19]. Moreover, alleles remain fixed between individuals and are not influenced by the onset or progression of disease. Consequently, causal inferences derived from MR analyses are less susceptible to confounding and reverse causality biases [20, 21]. And with the growing number of GWAS data published by large consortia, MR studies can provide reliable results with a sufficient sample size [22]. In this study, we performed a two-sample bidirectional MR analysis to evaluate the causal relationship between hypothyroidism and frozen shoulder.

Methods

Study design description

The bidirectional MR design, which examines the relationship between hypothyroidism and frozen shoulder, is succinctly outlined in Fig. 1. Using summary data from Genome-Wide Association Studies (GWAS) datasets, we conducted two MR analyses to explore the potential reciprocal association between hypothyroidism and frozen shoulder. In the reverse MR analyses, Frozen Shoulder was considered as the exposure and Hypothyroidism as the outcome, while the forward MR analyses focused on Hypothyroidism as the exposure. Figure 1 illustrates the key assumptions of the MR analysis.

Fig. 1
figure 1

Description of the study design in this bidirectional MR study. A MR analyses depend on three core assumptions. B Research design sketches

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Data source

Genetic variants associated with Hypothyroidism were extracted from published Summary-level GWAS datasets provided by the FinnGen Consortium, using the “Hypothyroidism” phenotype in this study. The GWAS included 16380353 subjects, including 22997 cases and 175475 controls. Data for Frozen Shoulder were obtained from the GWAS, which was derived from a European sample [23]. The frozen shoulder was defined based on the occurrence of one or more International Classification of Disease, 10th Revision (ICD10) codes (as shown in the supplementary material). Our MR study was conducted using publicly available studies or shared datasets and therefore did not require additional ethical statements or consent.

Selection of IV

For MR studies to yield reliable results, they must adhere to three fundamental assumptions [24], Regarding the IV selection, the following statements hold true: (1) IVs exhibit substantial correlation with exposure factors; (2) IVs do not directly impact outcomes but influence outcomes through exposure; (3) IVs are not correlated with any confounding factors that could influence exposure and outcome. Firstly, we selected single‐nucleotide polymorphisms (SNPs) from the European GWAS that met the genome-wide significance criterion (p < 5 × 10–8) and were associated with the exposure of interest as potential SNPs. Subsequently, we excluded any selected SNPs that linkage disequilibrium (LD) using the clump function (r2 = 0.001, kb = 10000). Furthermore, palindromic SNPs and ambiguous SNPs were excluded. These excluded SNPs were not included in subsequent analyses. To evaluate weak instrumental variable effects, we utilized the F-statistic, considering genetic variants with an F-statistic < 10 as weak IVs and excluding them. Then for the second assumption, we needed to manually remove SNPs associated with outcome (p < 5 × 10–8). For the third assumption, “ IVs are not correlated with any confounding factors that could influence exposure and outcome,” implying that the IVs chosen should not have horizontal pleiotropy. The final set of SNPs meeting these criteria were utilized as IVs in the subsequent MR analysis.

MR analysis

In this study, we evaluated the relationship between hypothyroidism and frozen shoulder using two different MR methods: IVW [25] and MR-Egger regression [26]. The Wald ratio for each IV will be meta-analyzed using the IVW approach to investigate the causal relationship. In contrast to the MR-Egger technique, which remains functional even in the presence of invalid IVs, the IVW method assumes that all included genetic variants are valid instrumental variables. Furthermore, MR-Egger incorporates an intercept term to examine potential pleiotropy. If this intercept term equals 0 (P > 0.05), the results of the MR-Egger regression model closely align with those obtained from IVW; However, if the intercept term deviates significantly from 0 (P < 0.05), it suggests possible horizontal pleiotropy associated with these IVs. MR-Egger employed as estimation method alongside IVW. Although less efficient, these approaches can provide reliable predictions across a broader range of scenarios.

Sensitivity analysis

We performed a sensitivity analysis to investigate potential horizontal pleiotropy and heterogeneity in our study, aiming to demonstrate the robustness of our findings. Cochran’s Q test was employed to identify possible heterogeneity. Cochran’s Q statistic assessed genetic variant heterogeneity while considering significance at p < 0.05 level and I2 > 25% as an indication of heterogeneity. on the results, we generated funnel plots. MR-Egger intercept tests were then utilized to estimate horizontal pleiotropy (with presence of an intercept and horizontal pleiotropy considered when p < 0.05). Additionally, a leave-one-out to determine if causality depended on or was influenced by any specific SNP. All statistical analyses were performed using the “TwoSampleMR” packages in R (version 3.6.3, www.r-project.org/) [27].

Results

Instrumental variables

We ultimately chose 39 SNPs as IVs for the final analysis after going through the aforementioned screening process. All IVs had an F-statistic > 10, indicating a low probability of weak IV bias. Comprehensive information on each IV can be found in Appendix 1.

Mendelian randomization results

According to the outcomes of the two MR techniques we employed for our analysis, hypothyroidism increases the risk factors for developing frozen shoulder. Specifically, as shown in the results of Table 1, the primary analytical outcome using the IVW method revealed an OR of 1.0577 (95% CI:1.0057–1.1123), P = 0.029. Additionally, employing the MR Egger method secondary analytical outcome resulted in an OR of 1.1608 (95% CI:1.0318–1.3060), P = 0.017. Furthermore, scatter plots (Fig. 2) and forest plots (Fig. 3) were generated based on the findings of this MR study.

Table 1 Causal associations between genetically determined hypothyroidism and frozen shoulder
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Fig. 2
figure 2

Scatterplot of MR analysis

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Fig. 3
figure 3

Forest plot of MR analysis

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Heterogeneity and sensitivity test

The heterogeneity of causal estimates obtained for each SNP reflects their variability. A lower level of heterogeneity indicates higher reliability of MR estimates. To further validate the dependability of the results, we conducted a sensitivity analysis to examine the heterogeneity in MR. The funnel plots we created are displayed in Fig. 4 together with the results of Cochran’s Q test (Table 2), which revealed no heterogeneity in IVs. Additionally, the MR-Egger intercept test results (p = 0.0968) indicated no presence of pleiotropy in our data. Furthermore, the outcomes leave-one-out test demonstrated that causation remained independent and unaffected by any specific SNP (Fig. 5).

Fig. 4
figure 4

Funnel plot to assess heterogeneity

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Table 2 Heterogeneity test results of this MR analysis
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Fig. 5
figure 5

Sensitivity analysis by the leave-one-out method

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Reverse Mendelian randomization analysis

In the reverse two-sample MR analysis, frozen shoulder was chosen as the exposure factor, and hypothyroidism as the outcome factor. The same threshold was set, and chain imbalance was eliminated. Finally, four SNPs were included as IVs in the reverse MR analysis. None of the four results from the MR analysis support a causal relationship between genetic susceptibility to frozen shoulder and the risk of hypothyroidism, as shown in Table 3.

Table 3 Causal associations between genetically determined frozen shoulder and hypothyroidism
Full size table

Discussion

The frequent shoulder ailment known as frozen shoulder is characterized by joint pain and dysfunction. It has a significant negative impact on patient’s quality of life and increases the financial strain on families and society. Frozen shoulder can be caused by various factors, with thyroid disorders being one of them, although the exact causal relationship between them remains unclear.

There is considerable debate over whether hypothyroidism enhances the prevalence of frozen shoulder in the population. Results from Carina Cohen et al. [4] indicate that thyroid disorders, particularly hypothyroidism and the presence of benign thyroid nodules, significantly contribute to the risk of developing frozen shoulder. These factors increase the likelihood of acquiring the condition by 2.69 times [4]. A case–control study conducted in China revealed that thyroid disease is associated with an elevated risk of developing frozen shoulder [14]. Hyung Bin Park et al. also discovered a notable association between subclinical hypothyroidism and frozen shoulder [16]. Consistent with previous studies, a case–control study from Brazil reported that patients with hypothyroidism were more likely to be diagnosed with frozen shoulder than comparable patients [28]. However, there are some inconsistencies. Kiera Kingston et al. [13] discovered hypothyroidism in 8.1% of individuals with adhesive capsulitis; however, this rate was lower than the 10.3% identified in the control population [13]. Hyung et al. concluded that there was no association between them [15]. Studies by Chris et al. also questioned the relationship between heart disease, high cholesterol and thyroid disease and frozen shoulder [29]. All of these studies, we discovered, had poor scores on the evidence-based medicine scale, were vulnerable to a wide range of confounding variables, and carried a number of significant risks of bias. Additionally, conventional observational studies only provide correlations rather than precise causal links.

To overcome this shortcoming, we performed the MR analysis. The results of the two MR methods examined in this study suggest a possible causal relationship between hypothyroidism and frozen shoulder. Importantly, no substantial heterogeneity or pleiotropy was observed in these findings. Our conclusions are similar to those of Deng et al. [30]. However, our study conducted a reverse Mendelian randomization analysis and had a larger sample size. Several mechanisms may underlie this association. First, fibrosis plays a crucial role in the movement disorders associated with frozen shoulder. Hypothyroidism impairs the synthesis and breakdown of collagen, elastic fibers, and polysaccharides within soft tissues, resulting in tissue edema and fibrosis, contributing to the development of frozen shoulder [31]. Second, hypothyroidism influences various signaling pathways including growth factors, the extracellular matrix, and calcium signaling, which can impact the differentiation and functionality of osteocytes, leading to bone degeneration and subsequently progressing to frozen shoulder [32]. Third, hypothyroidism can result in reduced nerve conduction velocity, nerve fiber degeneration, and neuritis, subsequently compromising the sensory and motor functions of nerves and elevating the risk of developing frozen shoulder [33]. The outcomes of the MR analysis can be used to screen potential risk factors in advance. Accordingly, people with hypothyroidism are more likely to develop frozen shoulder. It is suggested that clinicians should pay attention to the patients with shoulder discomfort when treating hypothyroidism, and provide some ideas for early intervention, which is beneficial to the prognosis of patients.

Our research has some advantages. Firstly, by employing the MR approach, confounding factors and reverse causality were carefully controlled, at least to a large extent. Secondly, our study relied on data derived from previously published GWAS studies, which boasted a substantial sample size and encompassed numerous genetic variants. Moreover, it is worth mentioning that we also used different methods to estimate the impacts, which improves the reliability of our results. However, our MR study still has limitations. First, there may be unobserved pleiotropy beyond vertical pleiotropy. In addition, the samples for this study were all from the European population. Research results based on race may limit their generalizations to other populations. Therefore, large-scale, multi ethnic clinical and basic research may be needed to validate these issues.

Conclusion

With the help of two Mendelian randomization studies, we found that there may be a causal relationship between hypothyroidism and frozen shoulder, and hypothyroidism may be associated with an increased risk of frozen shoulder. However, the exact mechanism remains to be elucidated. More research is required to investigate the underlying mechanisms of this causal relationship.

Availability of data and materials

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Abbreviations

MR:

Mendelian randomization

GWAS:

Genome-Wide Association Studies

IVW:

Inverse-Variance Weighted

OR:

Odds Ratio

CI:

Confidence Interval

IVs:

Instrumental Variables

SNPs:

Single‐Nucleotide Polymorphisms

LD:

Linkage Disequilibrium

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Acknowledgements

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Funding

This study was supported by the Project of State Key Laboratory of Radiation Medicine and Protection, Soochow University (No. GZK12023047).

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Authors and Affiliations

  1. Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, China

    Bin Chen, Zheng-hua Zhu, Zhi-cheng Zuo & Kai-long Zhou

  2. State Key Laboratory of Radiation Medicine and Protection, Soochow University, Suzhou, 215123, China

    Qing Li

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Contributions

BC: designed research, performed research, collected data, analyzed data, wrote paper. Zh Z, QL and Zc Z: collected data and verification results. Kl Z: designed research and revised article.

Corresponding author

Correspondence to Kai-long Zhou.

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Because the study was based on a public database, did not involve animal or human studies, and was available in the form of open access and anonymous data, Institutional Review Board approval was not required.

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Chen, B., Zhu, Zh., Li, Q. et al. Causal associations of hypothyroidism with frozen shoulder: a two-sample bidirectional Mendelian randomization study. BMC Musculoskelet Disord 25, 693 (2024). https://doi.org/10.1186/s12891-024-07826-y

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BMC Musculoskeletal Disorders

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